The Dataset Nutrition Label: A Framework To Drive Higher Data Quality Standards

Understand

Artificial intelligence (AI) systems built on incomplete or biased data will often exhibit problematic outcomes.

• Current methods of data analysis, particularly before model development, are costly and not standardized.
• The Dataset Nutrition Label (the Label) is a diagnostic framework that lowers the barrier to standardized data analysis by providing a distilled yet comprehensive overview of dataset "ingredients" before AI model development.
• Building a Label that can be applied across domains and data types requires that the framework itself be flexible and adaptable; as such, the Label is comprised of diverse qualitative and quantitative modules generated through multiple statistical and probabilistic modelling backends, but displayed in a standardized format.